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Ground segmentation , point cloud clustering based on CVC(Curved-Voxel-Clustering) and polygonal boxes

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my_detection

Ground segmentation , point cloud clustering based on CVC(Curved Voxel Clustering) and polygonal box(classify vehicles simply by length,width and height) 本项目使用设置地面坡度阈值的方法,滤除地面点,使用三维弯曲体素聚类法完成点云的聚类,包围盒参数由Apollo库的common_lib和object_builders_lib 得出,代码还有一些中文注释。 运行步骤:

git clone https://github.com/C-Xingyu/my_detection.git

cd my_detection

catkin_make -DCATKIN_WHITELIST_PACKAGES="common_lib"

catkin_make -DCATKIN_WHITELIST_PACKAGES="object_builders_lib"

catkin_make -DCATKIN_WHITELIST_PACKAGES="my_detection"

接下来配置launch文件(velodyne_points.launch) 运行

roslaunch my_detection velodyne_points.launch

2021-11-02 20-09-33 的屏幕截图

2021-11-02 20-38-47 的屏幕截图

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Ground segmentation , point cloud clustering based on CVC(Curved-Voxel-Clustering) and polygonal boxes


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Language:C++ 46.5%Language:Makefile 26.7%Language:CMake 11.9%Language:Python 11.5%Language:Shell 3.3%Language:TypeScript 0.1%Language:C 0.1%